Multimedia Tools and Applications

, Volume 76, Issue 1, pp 437–461 | Cite as

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

  • Wilder E. Castellanos
  • Juan C. Guerri
  • Pau Arce


Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks. Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.


Video evaluation framework Adaptive scalable video SVC video streaming Scalable video coding 


  1. 1.
    Akhshabi S, Begen AC, Dovrolis C (2011) An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In: Proceedings of the second annual ACM conference on Multimedia systems. ACM, pp 157–168Google Scholar
  2. 2.
    Alabdulkarim MN, Rikli N-E (2012) QoS Provisioning for H.264/SVC Streams over Ad-Hoc ZigBee Networks Using Cross-Layer Design. In: 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). pp 1–8Google Scholar
  3. 3.
    Birkos K, Tselios C, Dagiuklas T, Kotsopoulos S (2013) Peer selection and scheduling of H. 264 SVC video over wireless networks. In: Wireless Communications and Networking Conference (WCNC), 2013 IEEE. pp 1633–1638Google Scholar
  4. 4.
    Castellanos W (2014) SVCEval-RA - An Evaluation Framework for Adaptive Scalable Video Streaming. In: SourceForge Project. Accessed 1 May 2015
  5. 5.
    Castellanos W, Guerri JC, Arce P (2015) A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Comput Commun.
  6. 6.
    Castellanos W, Arce P, Acelas P, Guerri JC (2012) Route Recovery Algorithm for QoS-Aware Routing in MANETs. Springer Berlin Heidelberg, Bilbao, pp. 81–93Google Scholar
  7. 7.
    Chikkerur S, Sundaram V, Reisslein M, Karam LJ (2011) Objective video quality assessment methods: A classification, review, and performance comparison. Broadcast, IEEE Trans on 57:165–182CrossRefGoogle Scholar
  8. 8.
    Choupani R, Wong S, Tolun M (2014) Multiple description coding for SNR scalable video transmission over unreliable networks. Multimed Tools Appl 69:843–858. doi: 10.1007/s11042-012-1150-9 CrossRefGoogle Scholar
  9. 9.
    CISCO Corp. (2014) Cisco Visual Networking Index Forecast and Methodology. In: White Paper.
  10. 10.
    Dai M, Zhang Y, Loguinov D (2009) A unified traffic model for MPEG-4 and H. 264 video traces. IEEE Trans Multimedia 11:1010–1023CrossRefGoogle Scholar
  11. 11.
    Detti A, Bianchi G, Pisa C, et al. (2009) SVEF: an open-source experimental evaluation framework for H.264 scalable video streaming. In: IEEE Symposium on Computers and Communications. pp 36–41Google Scholar
  12. 12.
    Espina F, Morato D, Izal M, Magaña E (2014) Analytical model for MPEG video frame loss rates and playback interruptions on packet networks. Multimed Tools Appl 72:361–383. doi: 10.1007/s11042-012-1344-1 CrossRefGoogle Scholar
  13. 13.
    Fiems D, Steyaert B, Bruneel H (2012) A genetic approach to Markovian characterisation of H.264 scalable video. Multimedia Tools Appl 58:125–146CrossRefGoogle Scholar
  14. 14.
    Floyd S, Handley M, Kohler E Datagram Congestion Control Protocol (DCCP). Accessed 17 Feb 2014
  15. 15.
    Floyd S, Padhye J, Widmer J TCP Friendly Rate Control (TFRC): Protocol Specification. Accessed 17 Feb 2014
  16. 16.
    Fraz M, Malkani YA, Elahi MA (2009) Design and implementation of real time video streaming and ROI transmission system using RTP on an embedded digital signal processing (DSP) platform. In: 2nd International Conference on Computer, Control and Communication, 2009. IC4 2009. pp 1–6Google Scholar
  17. 17.
    ISO/IEC (2014) Information technology - Dynamic adaptive streaming over HTTP (DASH) - Part 1: Media presentation description and segment formats.Google Scholar
  18. 18.
    ITU-T (2013) Rec. H.264 & ISO/IEC 14496-10 AVC. Advanced Video Coding for Generic Audiovisual Services.Google Scholar
  19. 19.
    Ivrlač MT, Choi LU, Steinbach E, Nossek JA (2009) Models and analysis of streaming video transmission over wireless fading channels. Signal Process Image Commun 24:651–665. doi: 10.1016/j.image.2009.04.005 CrossRefGoogle Scholar
  20. 20.
    Karki R, Seenivasan T, Claypool M, Kinicki R (2010) Performance Analysis of Home Streaming Video Using Orb. In: Proceedings of the 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video. ACM, New York, NY, USA, pp 111–116Google Scholar
  21. 21.
    Ke C-H (2012) myEvalSVC-an Integrated Simulation Framework for Evaluation of H. 264/SVC Transmission. KSII Trans Internet Inf Syst (TIIS) 6:377–392. doi: 10.3837/tiis.2012.01.021 Google Scholar
  22. 22.
    Ke C-H, Shieh C-K, Hwang W-S, Ziviani A (2008) An Evaluation Framework for More Realistic Simulations of MPEG Video Transmission. J Inf Sci Eng 24:425–440Google Scholar
  23. 23.
    Klaue J, Rathke B, Wolisz A (2003) Evalvid–A framework for video transmission and quality evaluation. In: Computer Performance Evaluation. Modelling Techniques and Tools. Springer, pp 255–272Google Scholar
  24. 24.
    Le TA, Nguyen H (2014) End-to-end transmission of scalable video contents: performance evaluation over EvalSVC—a new open-source evaluation platform. Multimed Tools Appl 72:1239–1256. doi: 10.1007/s11042-013-1444-6 CrossRefGoogle Scholar
  25. 25.
    Lie A, Klaue J (2008) Evalvid-RA: trace driven simulation of rate adaptive MPEG-4 VBR video. Multimedia Systems 14:33–50. doi: 10.1007/s00530-007-0110-0 CrossRefGoogle Scholar
  26. 26.
    Moving Pictures Experts Group and ITU-T Video Coding Experts Group (2011) H. 264/SVC reference software (JSVM 9.19.14) and Manual.Google Scholar
  27. 27.
    Nightingale J, Wang Q, Grecos C (2014) Empirical evaluation of H.264/SVC streaming in resource-constrained multihomed mobile networks. Multimed Tools Appl 70:2011–2035. doi: 10.1007/s11042-012-1219-5 CrossRefGoogle Scholar
  28. 28.
    Parmar H, Thornburgh M (2012) Real-Time Messaging Protocol (RTMP) Specification. AdobeGoogle Scholar
  29. 29.
    Politis I, Dounis L, Dagiuklas T (2012) H. 264/SVC vs. H. 264/AVC video quality comparison under QoE-driven seamless handoff. Signal Process Image Commun 27:814–826CrossRefGoogle Scholar
  30. 30.
    Pozueco L, Pañeda XG, García R, et al. (2013) Adaptable system based on Scalable Video Coding for high-quality video service. Comput Electr Eng 39:775–789. doi: 10.1016/j.compeleceng.2013.01.015 CrossRefGoogle Scholar
  31. 31.
    Pozueco L, Pañeda XG, García R, et al. (2014) Adaptation engine for a streaming service based on MPEG-DASH. Multimed Tools Appl 1–20. doi: 10.1007/s11042-014-2034-y
  32. 32.
    Schwarz H, Marpe D, Wiegand T (2007) Overview of the Scalable Video Coding Extension of the H.264/AVC Standard. IEEE Trans Circ Syst Video Technol 17:1103–1120. doi: 10.1109/TCSVT.2007.905532 CrossRefGoogle Scholar
  33. 33.
    Seo H-Y (2013) An Efficient Transmission Scheme of MPEG2-TS over RTP for a Hybrid DMB System. ETRI J 35:655–665. doi: 10.4218/etrij.13.0112.0124 CrossRefGoogle Scholar
  34. 34.
    Sohn H, Yoo H, De Neve W, et al. (2010) Full-Reference Video Quality Metric for Fully Scalable and Mobile SVC Content. IEEE Trans Broadcast 56:269–280. doi: 10.1109/TBC.2010.2050628 CrossRefGoogle Scholar
  35. 35.
    Sousa-Vieira M-E (2011) Suitability of the M/G/∞ process for modeling scalable H.264 video traffic. In: Analytical and Stochastic Modeling Techniques and Applications. Springer, pp 149–158Google Scholar
  36. 36.
    Tanwir S, Perros H (2013) A Survey of VBR Video Traffic Models. IEEE Commun Surv Tutor 15:1778–1802. doi: 10.1109/SURV.2013.010413.00071 CrossRefGoogle Scholar
  37. 37.
    Tanwir S, Perros HG (2014) VBR Video Traffic Models. Wiley, HobokenCrossRefGoogle Scholar
  38. 38.
    The Network Simulator (NS-2). Accessed 6 Feb 2015
  39. 39.
    Unanue I, Urteaga I, Husemann R, et al. (2011) A Tutorial on H. 264/SVC Scalable Video Coding and its Tradeoff between Quality, Coding Efficiency and Performance. Recent Advances on Video Coding 1–24.Google Scholar
  40. 40.
    Van der Auwera G, David PT, Reisslein M, Karam LJ (2008) Traffic and quality characterization of the H. 264/AVC scalable video coding extension. Adv Multimedia 2008:1CrossRefGoogle Scholar
  41. 41.
    Wang Y, Claypool M (2005) RealTracer—Tools for Measuring the Performance of RealVideo on the Internet. Multimed Tools Appl 27:411–430. doi: 10.1007/s11042-005-3757-6 CrossRefGoogle Scholar
  42. 42.
    Wang Z, Lu L, Bovik AC (2004) Video quality assessment based on structural distortion measurement. Signal Process Image Commun 19:121–132. doi: 10.1016/S0923-5965(03)00076–6Google Scholar
  43. 43.
    Wien M, Schwarz H, Oelbaum T (2007) Performance Analysis of SVC. IEEE Trans Circ Syst for Video Technol 17:1194–1203. doi: 10.1109/TCSVT.2007.905530 CrossRefGoogle Scholar
  44. 44.
    YUV video repository. Accessed 10 Jan 2013

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Wilder E. Castellanos
    • 1
  • Juan C. Guerri
    • 1
  • Pau Arce
    • 1
  1. 1.Institute of Telecommunications and Multimedia Applications (iTEAM)Universitat Politècnica de ValènciaValenciaSpain

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